in this paper, the linearly conforming enriched radial basis point interpolation method is implemented for the elasto-plastic analysis of discontinuous medium. the linear conformability of the method is satisfied by the application of stabilized nodal integration and the enrichment of radial basis functions is achieved by the addition of linear polynomial terms. to implement the method for the ...

in the most described maximum power point tracking (mppt) methods in the literatures, the optimal operation point of the photovoltaic (pv) systems is estimated by linear approximations. however, these approximations can lead to less optimal operating conditions and significantly reduce the performances of the pv systems. this paper proposes a new approach to determine the maximum power point (m...

The material point method (MPM) is a meshfree mixed Lagrangian-Eulerian method which utilizes moving Lagrangian material points that store physical properties of a deforming continuum and a fixed Eulerian finite element mesh to solve the equations of motion for individual time steps. MPM proved to be successful in simulating mechanical problems which involve large deformations of history-depend...

This paper presents a statistical method to match feature points from stereo pairs of images. The proposed method is evaluated in terms of effectiveness, robustness and computational speed. The evaluation was performed on several pairs of real stereo images of natural scenes taken onboard an unmanned aerial vehicle. The results show that the proposed method reduces the number of incorrect match...

In this short survey, I revisit the role of the proximal point method in large scale optimization. I focus on three recent examples: a proximally guided subgradient method for weakly convex stochastic approximation, the prox-linear algorithm for minimizing compositions of convex functions and smooth maps, and Catalyst generic acceleration for regularized Empirical Risk Minimization.

A recent trend in probabilistic inference emphasizes the codification of models in a formal syntax, with suitable high-level features such as individuals, relations, and connectives, enabling descriptive clarity, succinctness and circumventing the need for the modeler to engineer a custom solver. Unfortunately, bringing these linguistic and pragmatic benefits to numerical optimization has prove...

In this paper we present a redesign of a linear algebra kernel of an interior point method to avoid the explicit use of problem matrices. The only access to the original problem data needed are the matrix-vector multiplications with the Hessian and Jacobian matrices. Such a redesign requires the use of suitably preconditioned iterative methods and imposes restrictions on the way the preconditio...

Let $C$ be a nonempty closed convex subset of a real Hilbert space $H$. Let ${S_n}$ and ${T_n}$ be sequences of nonexpansive self-mappings of $C$, where one of them is a strongly nonexpansive sequence. K. Aoyama and Y. Kimura introduced the iteration process $x_{n+1}=beta_nx_n+(1-beta_n)S_n(alpha_nu+(1-alpha_n)T_nx_n)$ for finding the common fixed point of ${S_n}$ and ${T_n}$, where $uin C$ is ...